Oseltamivir, Lopinavir/ritonavir and Reduning May Improve Survival of COVID-19 Patients With High-risk

No therapeutics have demonstrated specic ecacy for patients with COVID-19. We retrospectively evaluated 351 patients with COVID-19 admitted to the Third People's Hospital of Yichang from 9 January to 25 March, 2020.Univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression were employed to identify risk factors associated with progression, which were then incorporated into the nomogram. Survival of patients between high-risk and low-risk groups was compared by kaplan-Meier analysis. Moreover, we assessed the effects of existing common drugs on survival of patients with high-risk.

There is an urgent need to early identify factors that can predict the exacerbation and survival of COVID- 19 patients, and to screen potentially effective therapeutic drugs from existing drugs.
Hence, the present aims to provide a clue for the early identi cation and screening of high-risk COVID-19 patients who may rapid progress by constructing a nomogram, and to perform a comprehensive exploration of the e cacy of existing common drugs so as to provide ideas for clinical trial research.

Study participants
All

Data Collection
Clinical and laboratory data was obtained using standardized forms. Candidate variables were derived from electronic medical records which included demographic variables, including age, gender, and smoking history; clinical symptoms or signs; comorbid conditions, including diabetes mellitus (DM), hypertension, coronary heart disease (CHD), cardiovascular disease (CVD), chronic obstructive pulmonary disease (COPD), cancer, immunode ciency; and laboratory variables from blood. Laboratory assessments consisted of a complete blood count, blood coagulation function, tests of liver and renal function, C-reactive protein (CRP), procalcitonin (PCT), lactate dehydrogenase (LDH), and creatine kinase (CK).

Statistical analysis
Continuous variables were expressed as mean ± standard deviation (SD) if they were normally distributed or median and interquartile (IQR) if not, and categorical variables were described as number and proportion (%). The complete dataset was randomly separated into training and validation datasets (the split ratio was 7:3). In the training set, candidate predictors with signi cant P values in univariate logistic regression analysis were screened by the least absolute shrinkage and selection operator (LASSO) regression analysis to identify the best subset of features using glmnet package in R [11]. The lambda parameter that minimised expected model deviance was selected. The coe cients for each feature provided by LASSO regression model were used to generate the nomogram.
The performance of nomogram was assessed by receiver operating characteristic (ROC) analysis and the area under the curve (AUC) with 95% con dence interval (CI), calibration plot combined with the Hosmer-Lemeshow (HL) test [12], and decision curve analysis (DCA) [13]. Then, the performance of nomogram was further validated in the validation dataset and total dataset using the same methods described above. Kaplan-Meier curves were employed to determine the differences in survival between different groups of COVID-19 patients. The Log-rank test was performed to compare the survival curves. Data analysis was conducted by SPSS Statistics software (v20.0, SPSS, USA) and R software (version 3.6.0). P values less than 0.05 were considered to be statistically signi cant.

Characteristics Of The Patients
A total of 360 records were collected in the dataset. 9 records were excluded, of which 6 were duplicate and 3 were lack of laboratory data. Finally, 351 patients with COVID-19 were eligible for this retrospective study. Of these, we randomly selected 246 subjects (70%) into the training dataset, and the remaining 105 subjects (30%) were assigned to the validation dataset. The clinical characteristics of the training and validation datasets are summarized in Table 1. Based on univariate logistic analysis of the training cohort, we identi ed 24 variables signi cantly associated with risk of progression (Table 2). Of the relevant variables, 4 predictive factors (including WBC, CRP, whether lymphocyte ≥ 0.8 × 10 9 /L, and whether LDH ≥ 400 U/L) identi ed by LASSO regression were shown as a nomogram (Fig. 1a). In the training cohort, the AUC of our nomogram was 0.945 (95%CI: 0.91-0.98) (Fig. 1b). The calibration curve of our nomogram for the probability of exacerbation in the training dataset demonstrated good agreement between the predicted and observed risks (Fig. 1c). The Hosmer-Lemeshow test yielded a nonsigni cant statistic (Chi-square = 7.951, P value = 0.539). We performed DCA to assess the clinical value of the nomogram (Fig. 1d). The DCA curve showed that, if the threshold probability of 30-80%, using this nomogram to identify patients who might aggravate would be more bene t than either "treat-all" or "treat-no" schemes. The validation of nomogram for predicting the probability of the exacerbation of patients with COVID-19 was provided in the Supplementary material and Fig. S1.

Nomogram For Predicting The Survival Of Patients With Covid-19
According to the nomogram developed in the training cohort, the total point of each of the 322 patients in the total cohort was calculated, and another 29 cases were excluded due to lack of information. Based on a total pointof 160 on the nomogram, corresponding to a 50%probability of disease progression, it was de ned as the cut-off value. Patients in the total cohort were strati ed into low-risk group (total point < 160, n = 289) and high-risk group (total point ≥ 160, n = 33). Median follow-up was 56 days. Kaplan-Meier analysis demonstrated a signi cant difference in the overall survival (OS) rates between high-risk group and low-risk group. The 8-week survival rate was 71.41% in the high-risk group, while all patients in lowrisk group survived (Log-rank P < 0.0001, Fig. 1e). Time-dependent ROC curve analysis using timeROC package in R software showed that the nomogram achieved an AUC value of 0.96 (95%CI: 0.931-0.989) at 8-week of OS (Fig. 1f), demonstrating excellent performance of this nomogram for predicting survival of patients with COVID-19.

Effects of antiviral drugs on the survival of COVID-19 patients with high-risk
As all patients with low-risk were alive, we selected the high-risk patients (n = 33) to analyze the effects of drugs on the survival of patients with COVID-19. Of these patients, 9.1%, 24.2% and 66.7% were Mild type, Severe type and Critical type, respectively. Mean age was 66.8 years and median follow-up was 58 days.

Effects of Chinese patent medicine injections on the survival of COVID-19 patients with high-risk
In China, three Chinese patent medicine injections (including Reduning injection, Xuebijing injection, and Tanreqing injection) have been used in the treatment of patients with COVID-19. The 8-week survival rate was higher in the Reduning group than the no Reduning group (100% vs. 59.14%, Log-rank P < 0.01, Fig. 3a), while lower in the Xuebijing group than the no Xuebijing group (59.7% vs. 100%, Log-rank P < 0.01; Fig. 3b). There was no difference in OS between patients treated with and without Tanreqing injection (Log-rank P = 0.17; Fig. 3c).

Effects of other drugs on the survival of COVID-19 patients with high-risk
As COVID-19 patients are seriously ill, various drugs may be always applied simultaneously. We found that OS at 8-week was shorter in the antifugal therapy group compared tothe no antifungal therapy group (48.61% vs. 84.71%, Log-rank P < 0.01; Fig. S3a). There were no signi cant differences in OS of COVID-19 patients whether they received with glucocorticoids, thymalfasin, intravenous immunoglobulin (IVIG), or ambroxol ( Fig. S3b-e). Because all high-risk patients were treated with antibacterials, we cannot analyze the impact of antibacterials on survival.
Effects of the different combinations of oseltamivir, lopinavir/ritonavir and Reduning injection on the survival of COVID-19 patients with high-risk Based on the above results, we further analyzed the effects of the different combinations of oseltamivir, lopinavir/ritonavir and Reduning injection on the survival of COVID-19 patients with high-risk.
As shown in Fig. 4a, patients treated with the combination of oseltamivir and lopinavir/ritonavir had longer OS than those who treated without oseltamivir and lopinavir/ritonavir (8-week survival rate: 84.38% vs. 20.0%, Log-rank P < 0.01), while those with oseltamivir alone or with lopinavir/ritonavir alone did not have longer OS (Log-rank P = 0.15 and P = 0.23, respectively). Patients treated with the combination of oseltamivir and Reduning or with oseltamivir alone exhibited better OS than those without oseltamivir and Reduning (8-week survival rate: 100% vs. 26.67%, Log-rank P < 0.001; 77.92% vs. 26.67%, Log-rank P < 0.01; respectively), while those with Reduning alone did not exhibit better OS (Log-rank P = 0.073) (Fig. 4b). The 8-week survival rates of patients treated with the combination of lopinavir/ritonavir and Reduning or with lopinavir/ritonavir alone were longer than those without lopinavir/ritonavir and Reduning (100% vs. 26.67%, Log-rank P < 0.01; 70.1% vs. 26.67%, Log-rank P < 0.01; respectively), while that of patients treated with Reduning alone was not longer than that of those without lopinavir/ritonavir and Reduning (Log-rank P = 0.073) (Fig. 4c). As shown in the Fig. 4d, patients treated with the combination of these three drugs exhibited better OS than those without these three drugs or with single drug (7-week survival rate: 100% vs. 25.0%, Log-rank P < 0.001; 8-week survival rate: 100% vs. 66.67%, Log-rank P = 0.048; respectively), but not better than that of two drugs (8-week survival rate: 100% vs. 78.79%, Log-rank P = 0.13).

Discussion
In our study, we constructed a novel nomogram incorporated 4 simple and common predictors, including WBC, CRP, whether lymphocyte ≥ 0.8 × 10 9 /L, and whether LDH ≥ 400 U/L. Because there were 24 variables associated with the progression of COVID-19 in univariate logistic regression analysis, we used LASSO regression for construction of prediction nomogram. LASSO regression is suitable for the regression of high-dimensional data and used to screen the optimal combination of predictors from the primary dataset [11], markedly raised the accuracy of the exacerbation risks in patients with COVID-19.
The ROC analysis showed that the AUC of our nomogram was 0.945, indicating outstanding performance for prediction. Thus, our model may have a strong clinical transformation value. To evaluate the prognostic value of nomogram, we strati ed patients with COVID-19 into high-risk group and low-risk group with signi cantly different survival rate. It was noteworthy that all patients in the low-risk group were alive. The AUC at 8-week of ROC was 0.959, indicating excellent performance of predicting survival.
We further explored effects of drugs on the survival of patients with high-risk. This is the rst comprehensive report on effects of existing common drugs on the survival of patients with COVID-19.
Among them, we found oseltamivir, lopinavir/ritonavir and Reduning injection improved the survival of patients. Oseltamivir is indicated for the treatment and prophylaxis of seasonal in uenza, and it is not recommended by the plan of diagnosis and treatment for COVID-19 (Trial version seventh) [10]. However, a recent research reported that 3 of 4 patients with COVID-19 received oseltamivir, and all clinical symptoms and CT imaging abnormalities had resolved. All these 4 patients had 2 consecutive negative RT-PCR test results, indicating oseltamivir appeared to inhibit the ability of the virus to multiply in a patient's body.
Whether lopinavir/ritonavir can be used in the treatment of COVID-19 has attracted much attention. A recent trial of lopinavir/ritonavir showed that it did not signi cantly accelerate clinical improvement, and reduce mortality in adults hospitalized with severe COVID-19 [7]. However, when using our nomogram to distinguish high-risk patients, we found that lopinavir/ritonavir may improve their survival. The possible explanation for the inconsistency is thatlopinavir/ritonavir has no bene ts for low-risk patients, which may cover up its bene ts for high-risk patients.
In this study, we also found that a Chinese patent drug Reduning may be effective in the treatment of COVID-19. Previous animal study reported that Reduning administration signi cantly decreased both IL-6 and IL-10 production in severe pneumonia induced by in uenza A virus (H1N1) [17]. Reduning is a traditional Chinese medicine (TCM) injection re ned from three Chinese herbal medicines, namely, artemisiae annuae, honeysuckle, and gardenia, formulated for injection. Among them, artemisia annua is a kind of herb that was rst introduced in traditional Chinese medicine 1000 years ago. Artemisia annua has been reported to play an important role in immunomodulation [18,19], which may be the reason for the effective treatment of severe COVID-19 due to cytokine storm. The detail mechanism of the drug is worth of further study.
We additionally analyzed the effects of different combinations of these three drugs on the survival of COIVD-19 patients with high-risk. We found all the different combinations of drugs showed the effects of improving survival, although single drug may not show the effect in different grouping analysis. Another reason may be that the drugs may exert a therapeutic effect through synergy. Patients treated with the combination of these three drugs exhibited better OS than those without these three drugs or with single drug, but not better than that of two drugs, which may be related to the small number of high-risk cases in this study. Based on the above results, the combination of oseltamivir, lopinavir/ritonavir and Reduning injection may be a promising treatment for COVID-19 patients with high-risk.
There were some limitations to the present study. Firstly, our study was a retrospective study from one center. As lack of external validation in other population, the generalization of our predicting nomogram should be further validated. Secondly, it is di cult to distinguish the speci c e cacy of one single drug as various treatments were applied simultaneously. Thirdly, interpretation of this study is limited by the small size of the cohort.

Conclusions
In summary, the combination of oseltamivir, lopinavir/ritonavir and Reduning may improve survival of            The combination of oseltamivir, lopinavir/ritonavir, and Reduning injection.